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Research on the energy control of a dual-motor hybrid vehicle during engine start-stop process

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  • Tang, Xiaolin
  • Zhang, Dejiu
  • Liu, Teng
  • Khajepour, Amir
  • Yu, Haisheng
  • Wang, Hong

Abstract

In this paper, motor torque control methods are proposed to suppress the vibration of a dual-motor hybrid powertrain during start-stop operation. Firstly, a co-simulation ADAMS and MATLAB/SIMULINK model is built to study the dynamic characteristics of the hybrid vehicle during modes switching process. Secondly, a torque compensation control method of electric motors is established to compensate the vibration energy source. Thirdly, a vibration transfer path control is built to change the dynamic properties during the engine start-stop process. The results show that the proposed methods can reduce the longitudinal acceleration amplitude of the vehicle to less than 0.4 m/s2, which is only about 30% of the uncontrolled system, during the engine start process. While in the engine stop process, the longitudinal acceleration amplitude of the vehicle is reduced to less than 0.3 m/s2, and the vibration amplitude is only about 20% of the unchanged system. The established methods are effective for suppressing the vehicle vibration and controlling the energy during the modes switching.

Suggested Citation

  • Tang, Xiaolin & Zhang, Dejiu & Liu, Teng & Khajepour, Amir & Yu, Haisheng & Wang, Hong, 2019. "Research on the energy control of a dual-motor hybrid vehicle during engine start-stop process," Energy, Elsevier, vol. 166(C), pages 1181-1193.
    • Handle: RePEc:eee:energy:v:166:y:2019:i:c:p:1181-1193
    DOI: 10.1016/j.energy.2018.10.130
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    References listed on IDEAS

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    1. Millo, F. & Cubito, C. & Rolando, L. & Pautasso, E. & Servetto, E., 2017. "Design and development of an hybrid light commercial vehicle," Energy, Elsevier, vol. 136(C), pages 90-99.
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    Cited by:

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    5. Chen, Chien-fei & Zarazua de Rubens, Gerardo & Noel, Lance & Kester, Johannes & Sovacool, Benjamin K., 2020. "Assessing the socio-demographic, technical, economic and behavioral factors of Nordic electric vehicle adoption and the influence of vehicle-to-grid preferences," Renewable and Sustainable Energy Reviews, Elsevier, vol. 121(C).
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    10. Tian, Xiang & Cai, Yingfeng & Sun, Xiaodong & Zhu, Zhen & Xu, Yiqiang, 2019. "An adaptive ECMS with driving style recognition for energy optimization of parallel hybrid electric buses," Energy, Elsevier, vol. 189(C).
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    12. Du, Guodong & Zou, Yuan & Zhang, Xudong & Kong, Zehui & Wu, Jinlong & He, Dingbo, 2019. "Intelligent energy management for hybrid electric tracked vehicles using online reinforcement learning," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    13. Gao, Mingyuan & Wang, Yuan & Wang, Yifeng & Yao, Ye & Wang, Ping & Sun, Yuhua & Xiao, Jieling, 2020. "Modeling and experimental verification of a fractional damping quad-stable energy harvesting system for use in wireless sensor networks," Energy, Elsevier, vol. 190(C).
    14. Qin, Yechen & Tang, Xiaolin & Jia, Tong & Duan, Ziwen & Zhang, Jieming & Li, Yinong & Zheng, Ling, 2020. "Noise and vibration suppression in hybrid electric vehicles: State of the art and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).

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